Feb 13, 2018 · Abstract:Deep learning models with convolutional and recurrent networks are now ubiquitous and analyze massive amounts of audio, image, ...
Concise and expressive. 2. Specializing a polyhedral intermediate representation and its compilation algorithms to the domain of deep learning.
Jun 29, 2018 · Deep learning models with convolutional and recurrent networks are now ubiq- uitous and analyze massive amounts of audio, image, video, ...
Tensor Comprehensions provides framework-agnostic abstractions for High-Performance Machine Learning. Index. What is Tensor Comprehensions? Semantics · Range ...
Apr 28, 2023 · Tensor Comprehensions (TC) is a fully-functional C++ library to automatically synthesize high-performance machine learning kernels using Halide, ISL and NVRTC ...
Oct 14, 2021 · Bibliographic details on Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions.
A language close to the mathematics of deep learning called Tensor Comprehensions offering both imperative and declarative styles, a polyhedral Just-In-Time ...
Feb 14, 2018 · "Tensor Comprehensions": a DSL for automatically writing & evolutionarily optimizing new CUDA kernels, based on Halide, ...
Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions by Nicolas Vasilache et al., arXiv 2018; Intel nGraph: An ...
Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions · 4 code implementations • 13 Feb 2018 • Nicolas Vasilache, Oleksandr ...